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Tight sandstone reservoirs basically have low porosity and permeability, a complex pore structure and a heterogeneous distribution of immiscible fluids. With the development of theoretical models, it is common to characterize rock properties, i.e., pore structure, microfractures, fluid type and saturation, etc., based on acoustic and electrical properties. We have taken four tight sandstone samples and performed X-ray diffraction and cast thin section analyses. We measure porosity and permeability as well as ultrasonic properties and electrical conductivity at different confining pressures and fluid saturations. These measurements show that the P-wave velocity, P-wave attenuation and conductivity strongly depend on the type and saturation of the fluid and the microstructure of the rock. We propose a combined acoustic-electrical model based on the concept of equivalent medium and on the double porosity, patchy saturation and squirt flow models. We then create rock physics templates calibrated with wellbore log data to estimate fluid saturation and equant and soft porosities, which are well corroborated by gas production reports. This work demonstrates the link between combined acoustic-electrical responses and rock properties and provides an effective approach for applications in reservoirs. [ABSTRACT FROM AUTHOR]

In the field of Granular Computing (GrC), feature selection is an attractive task. Some basics of GrC such as information granulation and granularity have well guided the explorations of feature selection technique. Nevertheless, some challenges to perform feature selection such as high computational costs of repeating information granulation and multi-granularity structure in the process of searching qualified features may also arise. In this study, to improve the efficiency and effectiveness of feature selector, a novel framework named Glee : Granularity fiLter for fEature sElection , is reported. Firstly, the value of granularity related to each feature is calculated. Secondly, all features are reordered by the corresponding values of granularity. Finally, following such a derived sequence, features will be added into the selection pool one by one until the termination condition is achieved. Glee can not only eliminate the iterative calculations of information granulation in the whole process of selecting, but also provide sequence of features which may be insensitive to data perturbation. It should also be emphasized that Glee is a general framework, and most existing termination conditions to feature selection can be embedded into it. To validate the effectiveness of Glee , it is compared with several well-established feature selection schemes in elapsed time of selecting features, stability of selected features and classification performance. Experimental results over 20 UCI datasets with both raw features and 3 different ratios of noisy features demonstrate that our framework is superior as it yields better robustness with satisfactory elapsed time. [ABSTRACT FROM AUTHOR]

Understanding the effect that multiscale heterogeneities have on the wave responses of rocks at different frequencies is essential in the interpretation of seismic data. In fact, the behaviors of ultrasonic and seismic waves differ because the experiments involve different spatial scales. Then, a solution is to apply a theory that establishes a relation between the wave properties at different frequency bands considering a size range of heterogeneities. To investigate this problem, we have measured the compressional wave (P-wave) anelasticity (velocity and attenuation) of tight reservoir rocks at ultrasonic, sonic and seismic frequencies. The wave behavior as a function of porosity or clay content shows a consistent trend. With increasing confining pressure, the effect of porosity on attenuation decreases, while that of clay content gradually becomes important. To interpret the data, we propose a double-fractal poroelasticity model by incorporating the self-similarity characteristics of cracks and clay minerals. The comparison between the experimental data and model results reveals the fractality of the clay inclusions and cracks, with radii range of [10−6, 10−1.5] m and [10−6, 10−3.1] m, respectively, which is responsible for the anelastic behavior of the waves on a wide frequency band. [ABSTRACT FROM AUTHOR]

S-wave attenuation in porous media is affected by the presence and properties of saturating fluids. We measured the ultrasonic S-wave velocities of three types of tight rocks (siltstone, dolomite, and sandstone) under partial fluid saturation conditions using the pulse-transmission technique. The S-wave attenuation is estimated by the centroid frequency shift and spectral-ratio methods. The fluid-saturated test results show that the attenuation of most water-saturated dolomites is stronger than that of gas- or oil-saturated dolomites, whereas no apparent relationship exists between attenuation and fluid type in siltstone. The attenuation of siltstone and dolomite increases with increasing porosity and permeability, as well as with clay content for siltstone with clay contents less than 6%. The maximum attenuation of rocks partially saturated with gas and water occurs at high water saturation (55%–100%) in most siltstones. The attenuation of most dolomites shows an increasing trend with water saturation, but remains nearly unchanged in partially saturated sandstone. The attenuation of rocks partially saturated with oil and water is strongest at the partial saturation state in siltstone, but remains essentially constant with water saturation in dolomite. A squirt flow model is used to predict the S-wave attenuation of the fluid-saturated sample. Based on rock property and microstructure analyses, wave attenuation in the fluid-saturated rocks measured in this study can be explained by squirt flow mechanisms and the scattering effect owing to heterogeneities of water patches and grain clusters. [ABSTRACT FROM AUTHOR]